COLMARppm: A Web Server Tool for the Accurate and Rapid Prediction of 1H and 13C NMR Chemical Shifts of Organic Molecules and Metabolites.

Despite rapid progress in metabolomics research, a major bottleneck is the large number of metabolites whose chemical structures are unknown or whose spectra have not been deposited in metabolomics databases. Nuclear magnetic resonance (NMR) spectroscopy has a long history of elucidating chemical structures from experimentally measured 1H and 13C chemical shifts. One approach to characterizing the chemical structures of an unknown metabolite is to predict the 1H and 13C chemical shifts of candidate compounds (e.g., metabolites from the Human Metabolome Database (HMDB)) and compare them with chemical shifts of the unknown. However, accurate prediction of NMR chemical shifts in aqueous solution is challenging due to limitations of experimental chemical shift libraries and the high computational cost of quantum chemical methods. To improve NMR prediction accuracy and applicability, an empirical prediction strategy is introduced here to provide an accurately predicted chemical shift for organic molecules and metabolites within seconds. Unique features of COLMARppm include (i) the training library exclusively consisting of high quality NMR spectra measured under standard conditions in aqueous solution, (ii) utilization of NMR motif information, and (iii) leveraging of the improved prediction accuracy for the automated assignment of experimental chemical shifts for candidate structures. COLMARppm is demonstrated in terms of accuracy and speed for a set of 20 compounds taken from the HMDB for chemical shift prediction and resonance assignment. COLMARppm is applicable to a wide range of small molecules and can be directly incorporated into metabolomics workflows.

COLMAR1d: A Web Server for Automated, Quantitative One-Dimensional Nuclear Magnetic Resonance-Based Metabolomics at Arbitrary Magnetic Fields.

The field of metabolomics, which is quintessential in today's omics research, involves the large-scale detection, identification, and quantification of small-molecule metabolites in a wide range of biological samples. Nuclear magnetic resonance spectroscopy (NMR) has emerged as a powerful tool for metabolomics due to its high resolution, reproducibility, and exceptional quantitative nature. One of the key bottlenecks of metabolomics studies, however, remains the accurate and automated analysis of the resulting NMR spectra with good accuracy and minimal human intervention. Here, we present the COLMAR1d platform, consisting of a public web server and an optimized database, for one-dimensional (1D) NMR-based metabolomics analysis to address these challenges. The COLMAR1d database comprises more than 480 metabolites from GISSMO enabling a database query of spectra measured at arbitrary magnetic field strengths, as is demonstrated for spectra acquired between 1H resonance frequencies of 80 MHz and 1.2 GHz of mouse serum, DMEM cell growth medium, and wine. COLMAR1d combines the GISSMO metabolomics database concept with the latest tools for automated processing, spectral deconvolution, database querying, and globally optimized mixture analysis for improved accuracy and efficiency. By leveraging advanced computational algorithms, COLMAR1d offers a user-friendly, automated platform for quantitative 1D NMR-based metabolomics analysis allowing a wide range of applications, including biomarker discovery, metabolic pathway elucidation, and integration with multiomics strategies.

Holistic Prediction of AuNP Aggregation in Diverse Aqueous Suspensions Based on Machine Vision and Dark-Field Scattering Imaging.

The localized surface-plasmon resonance of the AuNP in aqueous media is extremely sensitive to environmental changes. By measuring the signal of plasmon scattering light, the dark-field microscopic (DFM) imaging technique has been used to monitor the aggregation of AuNPs, which has attracted great attention because of its simplicity, low cost, high sensitivity, and universal applicability. However, it is still challenging to interpret DFM images of AuNP aggregation due to the heterogeneous characteristics of the isolated and discontinuous color distribution. Herein, we introduce machine vision algorithms for the training of DFM images of AuNPs in different saline aqueous media. A visual deep learning framework based on AlexNet is constructed for studying the aggregation patterns of AuNPs in aqueous suspensions, which allows for rapid and accurate identification of the aggregation extent of AuNPs, with a prediction accuracy higher than 0.96. With the aid of machine learning analysis, we further demonstrate the prediction ability of various aggregation phenomena induced by both cation species and the concentration of the external saline solution. Our results suggest the great potential of machine vision frameworks in the accurate recognition of subtle pattern changes in DFM images, which can help researchers build predictive analytics based on DFM imaging data.

Triazine herbicide reduced the toxicity of the harmful dinoflagellate Karenia mikimotoi by impairing its photosynthetic systems.

Triazine herbicides are common contaminants in coastal waters, and they are recognized as inhibitors of photosystem II, causing significant hinderance to the growth and reproduction of phytoplankton. However, the influence of these herbicides on microalgal toxin production remains unclear. This study aimed to examine this relationship by conducting a comprehensive physiological and 4D label-free quantitative proteomic analysis on the harmful dinoflagellate Karenia mikimotoi in the presence of the triazine herbicide dipropetryn. The findings demonstrated a significant decrease in photosynthetic activity and pigment content, as well as reduced levels of unsaturated fatty acids, reactive oxygen species (ROS), and hemolytic toxins in K. mikimotoi when exposed to dipropetryn. The proteomic analysis revealed a down-regulation in proteins associated with photosynthesis, ROS response, and energy metabolism, such as fatty acid biosynthesis, chlorophyll metabolism, and nitrogen metabolism. In contrast, an up-regulation of proteins related to energy-producing processes, such as fatty acid ß-oxidation, glycolysis, and the tricarboxylic acid cycle, was observed. This study demonstrated that dipropetryn disrupts the photosynthetic systems of K. mikimotoi, resulting in a notable decrease in algal toxin production. These findings provide valuable insights into the underlying mechanisms of toxin production in toxigenic microalgae and explore the potential effect of herbicide pollution on harmful algal blooms in coastal environments.

Polystyrene microplastics exacerbated the toxicity of okadaic acid to the small intestine in mice.

Microplastics (MPs) and okadaic acid (OA) are known to coexist in marine organisms, potentially impacting humans through food chain. However, the combined toxicity of OA and MPs remains unknown. In this study, mice were orally administered OA at 200 µg/kg bw and MPs at 2 mg/kg bw. The co-exposure group showed a significant increase in malondialdehyde (MDA) content and significant decreases in superoxide dismutase (SOD) activity and glutathione (GSH) level compared to the control, MPs and OA groups (p < 0.05). Additionally, the co-exposure group exhibited significantly higher levels of IL-1ß and IL-18 compared to other groups (p < 0.05). These results demonstrated that co-exposure to MPs and OA induces oxidative stress and exacerbates inflammation. Histological and cellular ultrastructure analyses suggested that this combined exposure may enhance gut damage and compromise barrier integrity. Consequently, the concentration of OA in the small intestine of the co-exposure group was significantly higher than that in the OA group. Furthermore, MPs were observed in the lamina propria of the gut in the co-exposure group. Transcriptomic analysis revealed that the co-exposure led to increased expression of certain genes related to the NF-κB/NLRP3 pathway compared to the OA and MPs groups. Overall, this combined exposure may disrupt the intestinal barrier, and promote inflammation through the NF-κB/NLRP3 pathway. These findings provide precious information for the understanding of health risks associated with MPs and phycotoxins.

Predicting protein flexibility with AlphaFold.

AlphaFold2 has revolutionized protein structure prediction from amino-acid sequence. In addition to protein structures, high-resolution dynamics information about various protein regions is important for understanding protein function. Although AlphaFold2 has neither been designed nor trained to predict protein dynamics, it is shown here how the information returned by AlphaFold2 can be used to predict dynamic protein regions at the individual residue level. The approach, which is termed cdsAF2, uses the 3D protein structure returned by AlphaFold2 to predict backbone NMR NH S2 order parameters using a local contact model that takes into account the contacts made by each peptide plane along the backbone with its environment. By combining for each residue AlphaFold2's pLDDT confidence score for the structure prediction accuracy with the predicted S2 value using the local contact model, an estimator is obtained that semi-quantitatively captures many of the dynamics features observed in experimental backbone NMR NH S2 order parameter profiles. The method is demonstrated for a set nine proteins of different sizes and variable amounts of dynamics and disorder.

Systematic dissection of genomic features determining the vast diversity of conotoxins.

BACKGROUND: Conus, a highly diverse species of venomous predators, has attracted significant attention in neuroscience and new drug development due to their rich collection of neuroactive peptides called conotoxins. Recent advancements in transcriptome, proteome, and genome analyses have facilitated the identification of conotoxins within Conus' venom glands, providing insights into the genetic features and evolutionary patterns of conotoxin genes. However, the underlying mechanism behind the extraordinary hypervariability of conotoxins remains largely unknown. RESULTS: We analyzed the transcriptomes of 34 Conus species, examining various tissues such as the venom duct, venom bulb, and salivary gland, leading to the identification of conotoxin genes. Genetic variation analysis revealed that a subset of these genes (15.78% of the total) in Conus species underwent positive selection (Ka/Ks > 1, p < 0.01). Additionally, we reassembled and annotated the genome of C. betulinus, uncovering 221 conotoxin-encoding genes. These genes primarily consisted of three exons, with a significant portion showing high transcriptional activity in the venom ducts. Importantly, the flanking regions and adjacent introns of conotoxin genes exhibited a higher prevalence of transposon elements, suggesting their potential contribution to the extensive variability observed in conotoxins. Furthermore, we detected genome duplication in C. betulinus, which likely contributed to the expansion of conotoxin gene numbers. Interestingly, our study also provided evidence of introgression among Conus species, indicating that interspecies hybridization may have played a role in shaping the evolution of diverse conotoxin genes. CONCLUSIONS: This study highlights the impact of adaptive evolution and introgressive hybridization on the genetic diversity of conotoxin genes and the evolution of Conus. We also propose a hypothesis suggesting that transposable elements might significantly contribute to the remarkable diversity observed in conotoxins. These findings not only enhance our understanding of peptide genetic diversity but also present a novel approach for peptide bioengineering.

DNAzyme-Powered DNA Walker for Cooperative Expression Imaging of Mutant p53 and Telomerase in Cancer Cells.

Cooperative expression of multiple cancer biomarkers is of great significance in influencing cell pathways and drug treatment. However, the simultaneous analysis of low-abundance biomarkers in living cells remains a challenge. Here, we report a DNAzyme-powered DNA walker to visualize the cooperative expression of mutant p53 and telomerase in living cells. The activation of the DNA walker is orthogonally powered by mutated p53 and telomerase, which enables the unlocking of the walking strand and the subsequently repeated substrate cleavage, producing fluorescence recovery for the imaging of the two target molecules in living cells. The DNA walker allows for real-time monitoring of the expression profile of mutant p53 and active telomerase in cancer cells under various antitumor drug treatments, and the results demonstrate the cooperative expression of mutant p53 and telomerase via the Akt pathway, which may bring new insights into the study of cancer pathway-relevant biomarkers.

Amperometric Identification of Single Exosomes and Their Dopamine Contents Secreted by Living Cells.

Dopamine (DA) is an important neurotransmitter, which not only participates in the regulation of neural processes but also plays critical roles in tumor progression and immunity. However, direct identification of DA-containing exosomes, as well as quantification of DA in single vesicles, is still challenging. Here, we report a nanopipette-assisted method to detect single exosomes and their dopamine contents via amperometric measurement. The resistive-pulse current measured can simultaneously provide accurate information of vesicle translocation and DA contents in single exosomes. Accordingly, DA-containing exosomes secreted from HeLa and PC12 cells under different treatment modes successfully detected the DA encapsulation efficiency and the amount of exosome secretion that distinguish between cell types. Furthermore, a custom machine learning model was constructed to classify the exosome signals from different sources, with an accuracy of more than 99%. Our strategy offers a useful tool for investigating single exosomes and their DA contents, which facilitates the analysis of DA-containing exosomes derived from other untreated or stimulated cells and may open up a new insight to the research of DA biology.

Dual-Modal Apoptosis Assay Enabling Dynamic Visualization of ATP and Reactive Oxygen Species in Living Cells.

ATP and reactive oxygen species (ROS) are considered significant indicators of cell apoptosis. However, visualizing the interplay between apoptosis-related ATP and ROS is challenging. Herein, we developed a metal-organic framework (MOF)-based nanoprobe for an apoptosis assay using duplex imaging of cellular ATP and ROS. The nanoprobe was fabricated through controlled encapsulation of gold nanorods with a thin zirconium-based MOF layer, followed by modification of the ROS-responsive molecules 2-mercaptohydroquinone and 6-carboxyfluorescein-labeled ATP aptamer. The nanoprobe enables ATP and ROS visualization via fluorescence and surface-enhanced Raman spectroscopy, respectively, avoiding the mutual interference that often occurs in single-mode methods. Moreover, the dual-modal assay effectively showed dynamic imaging of ATP and ROS in cancer cells treated with various drugs, revealing their apoptosis-related pathways and interactions that differ from those under normal conditions. This study provides a method for studying the relationship between energy metabolism and redox homeostasis in cell apoptosis processes.

Efficient modulation of cellular phosphorus components in response to phosphorus deficiency in the dinoflagellate Karenia mikimotoi.

IMPORTANCE: Dinoflagellates are the most common phytoplankton group and account for more than 75% of harmful algal blooms in coastal waters. In recent decades, dinoflagellates seem to prevail in phosphate-depleted waters. However, the underlying acclimation mechanisms and competitive strategies of dinoflagellates in response to phosphorus deficiency are poorly understood, especially in terms of intracellular phosphorus modulation and recycling. Here, we focused on the response of intracellular phosphorus metabolism to phosphorus deficiency in the model dinoflagellate Karenia mikimotoi. Our work reveals the strong capability of K. mikimotoi to efficiently regulate intracellular phosphorus resources, particularly through membrane phospholipid remodeling and miRNA regulation of energy metabolism. Our research improved the understanding of intracellular phosphorus metabolism in marine phytoplankton and underscored the advantageous strategies of dinoflagellates in the efficient modulation of internal phosphorus resources to maintain active physiological activity and growth under unsuitable phosphorus conditions, which help them outcompete other species in coastal phosphate-depleted environments.

Carbon dots with hydrogen bond-controlled aggregation behavior.

Here, hydrophilic carbon dots (H-CDs) are prepared by a facile room temperature method. The strength of hydrogen bonds can be controlled by introducing proton and aprotic solvents, respectively, so as to realize the tunable aggregation state of H-CDs. Because of the ultrasensitive response to dimethyl sulfoxide (DMSO), H-CDs can serve as optical probes for detecting DMSO in a linear range of 0.005% to 0.75% and with a detection limit of 0.001%.

A rare presentation of central pontine myelinolysis secondary to hyperglycaemia.

BACKGROUND: Central pontine myelinolysis (CPM) is a rare demyelinating disorder caused by the loss of myelin in the center of the basis pontis. CPM typically occurs with rapid correction of severe chronic hyponatremia and subsequent disturbances in serum osmolality. Although hyperglycaemia is recognized as a pathogenetic factor in serum osmolality fluctuations, CPM is rarely seen in the context of diabetes. CASE PRESENTATION: A 66-year-old Chinese male presented with a history of gait imbalance, mild slurred speech and dysphagia for two weeks. MRI showed the mass lesions in the brainstem, and laboratory examinations showed high blood glucose and HbA1c, as well as increased serum osmolality. The patient was diagnosed with CPM secondary to hyperosmolar hyperglyceamia and received insulin treatment as well as supportive therapy. After six weeks of followup, the patient had fully recovered to a normal state. CONCLUSION: CPM is a potentially fatal neurological condition and can occur in uncontrolled diabetes mellitus. Early diagnosis and timely treatment are crucial for improving the prognosis.

Analysis of research status and trends on marine benthic dinoflagellate toxins: A bibliometric study based on web of science database and VOSviewer.

Marine benthic dinoflagellate toxins, potent bioactive compounds with wide-ranging presence in marine ecosystems, have surged in response to global climate change and human activities, prompting an urgent and imperative inquiry. This study conducts an in-depth review of contemporary research concerning these toxins, employing meticulous bibliometric analysis. Leveraging a dataset of 736 relevant literatures sourced from the Web of Science (spanning from 2000 to May 2023), our analysis delves comprehensively into the scientific discourse surrounding these toxic compounds. Employing tools such as VOSviewer, co-citation analysis, co-occurrence analysis, and cluster analysis, our study yields nuanced insights into the intricate characteristics and trajectories of the field. The co-citation analysis underscores the pivotal role played by benthic and epiphytic dinoflagellates like Ostreopsis and Gambierdiscus in shaping prevailing research trends. Our study identifies four distinct research directions, encompassing the domains of ecology, toxicology, toxin production, and taxonomy. Moreover, it traces the evolutionary journey of research stages, marking the transition from a focus on taxonomy to an emphasis on unraveling molecular mechanisms. The culmination of our comprehensive analysis yields three pertinent research recommendations: a call for widescale global studies, the advancement of rapid toxin monitoring techniques, and a deeper exploration of the factors influencing toxin synthesis and toxicity. These findings provide invaluable insights to researchers grappling with the complex realm of harmful algal blooms and substantially enrich the understanding of this pivotal and pressing field.

Association between ambient carbon monoxide levels and hospitalization costs of patients with myocardial infarction: Potential effect modification by ABO blood group.

Previous researches have reported the association between air pollution and various diseases. However, few researches have investigated whether air pollutants are associated with the economic loss resulting from patients' hospitalization, especially the economic loss of hospitalization due to acute cardiovascular events. The purpose of our research was to explore the association between the levels of carbon monoxide (CO), taken as an index of pollution, and the hospitalization costs of myocardial infarction (MI), and the potential effect modification by the ABO blood group. A total of 3237 MI inpatients were included in this study. A multiple linear regression model was used to evaluate the association between ambient CO levels and hospitalization costs of MI patients. Moreover, we performed stratified analyses by age, gender, body mass index (BMI), season, hypertension, and ABO blood types. There was a positive association between the levels of CO in the air and the costs of hospitalization caused by MI. Furthermore, such association was stronger in males, BMI ≥25, <65 years, with hypertension, and non-O blood group. Interestingly, we found the association was particularly significant in patients with blood group B. Overall, our study first found that ambient CO levels could have an impact on the hospitalization costs for MI patients, and those with blood group B can be more sensitive.

Exposure to okadaic acid could disrupt the colonic microenvironment in rats.

Okadaic acid (OA) is one of the most prevalent marine phycotoxin with complex toxicity, which can lead to toxic symptoms such as diarrhea, vomiting, nausea, abdominal pain, and gastrointestinal discomfort. Studies have shown that the main affected tissue of OA is digestive tract. However, its toxic mechanism is not yet fully understood. In this study, we investigated the changes that occurred in the epithelial microenvironment following OA exposure, including the epithelial barrier and gut bacteria. We found that impaired epithelial cell junctions, mucus layer destruction, cytoskeletal remodeling, and increased bacterial invasion occurred in colon of rats after OA exposure. At the same time, the gut bacteria decreased in the abundance of beneficial bacteria and increased in the abundance of pathogenic bacteria, and there was a significant negative correlation between the abundance of pathogenic bacteria represented by Escherichia/Shigella and animal body weight. Metagenomic analysis inferred that Escherichia coli and Shigella spp. in Escherichia/Shigella may be involved in the process of cytoskeletal remodeling and mucosal layer damage caused by OA. Although more evidence is needed, our results suggest that opportunistic pathogens may be involved in the complex toxicity of OA during OA-induced epithelial barrier damage.

Schiff Base Reaction in a Living Cell: In Situ Synthesis of a Hollow Covalent Organic Polymer To Regulate Biological Functions.

Artificially performing chemical reactions in living biosystems to attain various physiological aims remains an intriguing but very challenging task. In this study, the Schiff base reaction was conducted in cells using Sc(OTf)3 as a catalyst, enabling the in situ synthesis of a hollow covalent organic polymer (HCOP) without external stimuli. The reversible Schiff base reaction mediated intracellular Oswald ripening endows the HCOP with a spherical, hollow porous structure and a large specific surface area. The intracellularly generated HCOP reduced cellular motility by restraining actin polymerization, which consequently induced mitochondrial deactivation, apoptosis, and necroptosis. The presented intracellular synthesis system inspired by the Schiff base reaction has strong potential to regulate cell fate and biological functions, opening up a new strategic possibility for intervening in cellular behavior.

Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.

Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) designed for spectral peak picking are capable of deconvoluting highly crowded NMR spectra rivaling the facilities of human experts. Superior DNN-based peak picking is one of a series of critical steps during NMR spectral processing, analysis, and interpretation where machine learning is expected to have a major impact. In this perspective, we lay out some of the unique strengths as well as challenges of machine learning approaches in this new era of automated NMR spectral analysis. Such a discussion seems timely and should help define common goals for the NMR community, the sharing of software tools, standardization of protocols, and calibrate expectations. It will also help prepare for an NMR future where machine learning and artificial intelligence tools will be common place.

COLMARq: A Web Server for 2D NMR Peak Picking and Quantitative Comparative Analysis of Cohorts of Metabolomics Samples.

Highly quantitative metabolomics studies of complex biological mixtures are facilitated by the resolution enhancement afforded by 2D NMR spectra such as 2D 13C-1H HSQC spectra. Here, we describe a new public web server, COLMARq, for the semi-automated analysis of sets of 2D HSQC spectra of cohorts of samples. The workflow of COLMARq includes automated peak picking using the deep neural network DEEP Picker, quantitative cross-peak volume extraction by numerical fitting using Voigt Fitter, the matching of corresponding cross-peaks across cohorts of spectra, peak volume normalization between different spectra, database query for metabolite identification, and basic univariate and multivariate statistical analyses of the results. COLMARq allows the analysis of cross-peaks that belong to both known and unknown metabolites. After a user has uploaded cohorts of 2D 13C-1H HSQC and optionally 2D 1H-1H TOCSY spectra in their preferred format, all subsequent steps on the web server can be performed fully automatically, allowing manual editing if needed and the sessions can be saved for later use. The accuracy, versatility, and interactive nature of COLMARq enables quantitative metabolomics analysis, including biomarker identification, of a broad range of complex biological mixtures as is illustrated for cohorts of samples from bacterial cultures of Pseudomonas aeruginosa in both its biofilm and planktonic states.

Specially Resolved Single Living Cell Perfusion and Targeted Fluorescence Labeling Based on Nanopipettes.

Targeted delivery and labeling of single living cells in heterogeneous cell populations are of great importance to understand the molecular biology and physiological functions of individual cells. However, it remains challenging to perfuse fluorescence markers into single living cells with high spatial and temporal resolution without interfering neighboring cells. Here, we report a single cell perfusion and fluorescence labeling strategy based on nanoscale glass nanopipettes. With the nanoscale tip hole of 100 nm, the use of nanopipettes allows special perfusion and high-resolution fluorescence labeling of different subcellular regions in single cells of interest. The dynamic of various fluorescent probes has been studied to exemplify the feasibility of nanopipette-dependent targeted delivery. According to experimental results, the cytoplasm labeling of Sulfo-Cyanine5 and fluorescein isothiocyanate is mainly based on the Brownian movement due to the dyes themselves and does not have a targeting ability, while the nucleus labeling of 4',6-diamidino-2-phenylindole (DAPI) is originated from the adsorption between DAPI and DNA in the nucleus. From the finite element simulation, the precise manipulation of intracellular delivery is realized by controlling the electro-osmotic flow inside the nanopipettes, and the different delivery modes between nontargeting dyes and nucleus-targeting dyes were compared, showcasing the valuable ability of nanopipette-based method for the analysis of specially defined subcellular regions and the potential applications for single cell surgery, subcellular manipulation, and gene delivery.